Automated segmentation of MS lesions from multi-channel MR images

van Leemput, Koen and Maes, Frederik and Bello, Fernando and Vandermeulen, Dirk and Colchester, Alan C. F. and Suetens, Paul
(1999)
Automated segmentation of MS lesions from multi-channel MR images.
In: 2nd International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 99), Sep 19-22, 1999, Cambridge, England.
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Abstract

Quantitative analysis of AIR images is becoming increasingly important as a surrogate marker in clinical trials in multiple sclerosis (MS). This paper describes a fully automated model-based method for segmentation of MS lesions from multi-channel AIR images. The method simultaneously corrects for AIR field inhomogeneities, estimates tissue class distribution parameters and classifies the image voxels. MS lesions are detected as voxels that are not well explained by the model. The results of the automated method are compared with the lesions delineated by human experts, showing a significant total lesion load correlation and an average overall spatial correspondence similar to that between the experts.